Sam Altman says Meta offered OpenAI staffers $100M bonuses

Original Article ↗ Hacker News Discussion ↗

OpenAI’s Edge: Capital, Scale, and Productization vs. Unique Talent

  • Several commenters argue OpenAI’s core advantage is access to massive capital and willingness to burn it on scaling “standard” ML methods, not uniquely brilliant engineering.
  • They emphasize that large LLMs (e.g., LaMDA, GPT‑3) existed years before ChatGPT; the real breakthrough was human-feedback fine-tuning and safety layers that made LLMs controllable and marketable.
  • Many engineers at top labs are seen as somewhat fungible; the truly rare skills involve managing ultra-large-scale training and the organizational politics that enable that scale.

AI Hiring Market and the $100M Number

  • The software job market is described as “all or nothing”: extreme compensation for a tiny elite involved in cutting‑edge LLM training and infra, stagnation for most others.
  • High pay is justified not by difficulty of the basic math, but by the rarity of real-world experience training trillion‑parameter models, likened to experienced rocket engine designers.
  • Some think $100M likely applies to a very small number of individuals whose unvested OpenAI equity and future upside must be bought out, not generic “staffers.”

Strategic Gamesmanship Between Meta and OpenAI

  • One view: Meta is overpaying to cripple OpenAI by poaching its best people and forcing it to match insane offers, raising its cost structure.
  • Another: even publicizing such offers (true or not) pressures Meta’s own negotiations and incites OpenAI employees to demand more.
  • Some suggest Meta could partly “pay” in equity but others counter that equity and RSUs are real costs and visible to shareholders.

Money, Mission, and Ethics

  • Debate over whether people are “just in it for money” versus being motivated by mission, impact, colleagues, and frontier work.
  • Many note people routinely accept lower pay for passion or public service, but others see top AI talent as more akin to Wall Street—smart, heavily money‑motivated.
  • There is cynicism about Big Tech AI ethics: Meta is criticized for dystopian uses (AI friends, ad targeting), OpenAI for abandoning its “for good” and “open” origins.

Moats, Competition, and Who Innovates

  • Mega‑salaries are seen as reinforcing Big Tech moats: startups with even billions in funding can’t hire many such people if compensation normalizes near $100M.
  • Some believe real breakthroughs may still come from outsiders or smaller research groups not captured by these incentives.

Trust and Verifiability of Altman’s Claim

  • Multiple commenters question whether the $100M offers are true, calling Altman a skilled manipulator with a history of half‑truths.
  • They see the story as almost perfect PR: it flatters OpenAI, raises perceived talent value, and hinders Meta’s bargaining—while being nearly impossible for anyone to publicly refute.